How combining different caries lesions characteristics may be helpful in short-term caries progression prediction: model development on occlusal surfaces of primary teeth

Autor(es)

Floriano, Isabela ^{[1, 2]} ; Rocha, Elizabeth Souza ^[2] ; Matos, Ronilza ^{[1, 3]} ; Mattos-Silveira, Juliana ^[1] ; Ekstrand, Kim Rud ^[4] ; Mendes, Fausto Medeiros ^[1] ; Braga, Mariana Minatel ^[1]

Afiliação do(s) autor(es)

^[1] Univ Sao Paulo, Sch Dent, Dept Orthodont & Paediat Dent, Ave Prof Lineu Prestes, 2227, Cidade Univ, Sao Paulo, SP - Brazil

^[2] Univ Uninovafapi Ctr, Dent Course, Teresina, Piaui - Brazil

^[3] Fundacao Herminio Ometto, Dent Sch, Araras, SP - Brazil

^[4] Univ Copenhagen, Dent Sch Copenhagen, Sect Cariol & Endodont, Copenhagen - Denmark

• Tipo de documento: Artigo Científico
• Fonte: BMC ORAL HEALTH; v. 21, n. 1 MAY 12 2021.
• Citações Web of Science: 0

Resumo

Background Few studies have addressed the clinical parameters' predictive power related to caries lesion associated with their progression. This study assessed the predictive validity and proposed simplified models to predict short-term caries progression using clinical parameters related to caries lesion activity status. Methods The occlusal surfaces of primary molars, presenting no frank cavitation, were examined according to the following clinical predictors: colour, luster, cavitation, texture, and clinical depth. After one year, children were re-evaluated using the International Caries Detection and Assessment System to assess caries lesion progression. Progression was set as the outcome to be predicted. Univariate multilevel Poisson models were fitted to test each of the independent variables (clinical features) as predictors of short-term caries progression. The multimodel inference was made based on the Akaike Information Criteria and C statistic. Afterwards, plausible interactions among some of the variables were tested in the models to evaluate the benefit of combining these variables when assessing caries lesions. Results 205 children (750 surfaces) presented no frank cavitations at the baseline. After one year, 147 children were reassessed (70%). Finally, 128 children (733 surfaces) presented complete baseline data and had included primary teeth to be reassessed. Approximately 9% of the reassessed surfaces showed caries progression. Among the univariate models created with each one of these variables, the model containing the surface integrity as a predictor had the lowest AIC (364.5). Univariate predictive models tended to present better goodness-of-fit (AICs < 388) and discrimination (C:0.959-0.966) than those combining parameters (AIC:365-393, C:0.958-0.961). When only non-cavitated surfaces were considered, roughness compounded the model that better predicted the lesions' progression (AIC = 217.7, C:0.91). Conclusions Univariate model fitted considering the presence of cavitation show the best predictive goodness-of-fit and discrimination. For non-cavitated lesions, the simplest way to predict those lesions that tend to progress is by assessing enamel roughness. In general, the evaluation of other conjoint parameters seems unnecessary for all non-frankly cavitated lesions. (AU)

• Processo FAPESP: 13/27206-8 - Custo-efetividade, aplicabilidade e impacto na qualidade de vida da detecção e avaliação de lesões de cárie iniciais em dentes decíduos: estudo controlado randomizado
• Beneficiário: Isabela Floriano Nunes Martins
• Modalidade de apoio: Bolsas no Brasil - Doutorado
• Processo FAPESP: 11/16415-0 - Validade concorrente e preditiva de dois índices visuais para a avaliação da atividade das lesões de cárie em dentes decíduos
• Beneficiário: Isabela Floriano Nunes Martins
• Modalidade de apoio: Bolsas no Brasil - Mestrado